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ATB Approach and Methodology, 2021 

The Electricity ATB presents the cost and performance of typical electricity generation plants in the United States. It represents renewable electricity generation plants by either (1) reflecting the entire geographic range of resource with a few points averaging similar characteristics or (2) providing examples to demonstrate a range associated with resource potential. Foundational to this averaging approach, NREL uses high-resolution, location-specific resource data to represent site-specific capital investment and estimated annual energy production for all potential renewable energy plants in the United States.

For each renewable technology, the ATB data and website include:

For fossil (natural gas and coal) generation plants, the ATB data and website include:

  • Base Year estimates for parameters that include primary cost and performance metrics:
    • Capital expenditures (total overnight costs)
    • Fixed and variable operating expenditures
    • Operating range (expected availability, minimum emissions compliant load)
    • Full load design emissions rates for carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter (PM), and mercury (Hg)
  • Three scenarios for future technology innovation, and their associated parameter values
  • Descriptions of the resource, cost and performance estimation methodology, and data sources.

For nuclear generation plants, the ATB:

  • Relies on U.S. Energy Information Administration (EIA) representation of current year plant cost estimates and for plant cost projections through 2050 from AEO2021 (EIA, 2021)
  • Relies on EIA scenarios for fuel price projections through 2050 from AEO2021 (EIA, 2021); future work may include national laboratory projections for these technologies.

For biopower plants, the ATB:

  • Relies on EIA representation of current future plant cost estimates through 2050 from AEO2021 (EIA, 2021)
  • Represents the average biopower feedstock price based on the U.S. Billion Ton Update study (DOE, 2011)through 2030
  • Holds the biopower feedstock price at 2030 levels through 2050.

Base Year (2019) Costs in the ATB

Base year (2019) costs in the ATB are from the following sources:

Sources of Base Year Costs

TechnologySource
Land-based wind power plantsCapital expenditures (CAPEX) associated with wind plants installed in the interior of the country are used to characterize CAPEX for hypothetical wind plants with average annual wind speeds that correspond with the median conditions for recently installed wind facilities (Stehly et al., 2020). The operation and maintenance (O&M) of $43/kW-yr is estimated in the 2019 Cost of Wind Energy Review (Stehly et al., 2020); no variation of fixed operation and maintenance expenses (FOM) with wind speed class is assumed. Capacity factors align with performance in Wind Speed Classes 2–7, where most installations are located.
Offshore wind power plantsBase Year estimates are derived from a combination of bottom-up techno-economic cost modeling (Beiter et al., 2016) and experiential learning effects with economies of size and scale from higher turbine and plant ratings (Beiter et al., 2020). Bottom-up estimates from the 2020 ATB are brought forward one year (2018 to 2019) using the learning methodology.
Utility, commercial, and residential photovoltaic (PV) plantsCAPEX for 2019 are based on new bottom-up cost modeling and market data from (Feldman et al., 2021). O&M costs are based on modeled pricing for a 100-MWDC, one-axis tracking system (Feldman et al., 2021). Resource classes were expanded from 5 to 10 and capacity factors are now based on weighted averages within specific global horizontal irradiance (GHI) bins.
Concentrating solar power plantsBottom-up cost modeling are from (Turchi et al., 2019) for the updates to the System Advisor Model (SAM) cost components. `
Geothermal plantsBottom-up cost modeling use Geothermal Electricity Technology Evaluation Model (GETEM) and inputs from the GeoVision Business-as-Usual (BAU) scenario (DOE, 2019).
Hydropower plantsNon-powered dam (NPD) data are based on bottom-up new 2020 cost analysis (Oladosu, G. et al., 2021). New stream-reach development (NSD) data are retained from previous years and were based on Hydropower Vision study (DOE, 2016), with bottom-up cost modeling from the Hydropower Baseline Cost Modeling report (O'Connor et al., 2015).
Utility-scale PV-plus-battery CAPEX for 2019 are based on new bottom-up cost modeling and market data from (Feldman et al., 2021). O&M costs are based on modeled pricing for a 134-MWDC, one-axis tracking system coupled with 50-MW, 4-hour battery storage (Feldman et al., 2021). The chosen configuration reflects recent and proposed utility-scale PV-plus-battery projects. Capacity factors and tax credits assume 75% of the energy used to charge the battery component is derived from the coupled PV (on an annual basis).
Utility-scale, commercial, and residential battery storageCurrent costs for utility-scale battery energy storage systems (BESS) are based on a bottom-up cost model using the data and methodology for utility-scale BESS in (Feldman et al., 2021).
Pumped-storage hydropower plants (PSH)Resource characterizations with capital costs are forthcoming and will accompany the national closed-loop PSH resource assessment. O&M costs are from (Mongird et al., 2020).
Natural gas and coalEstimates of performance and costs for currently available fossil-fueled electricity generating technologies are representative of current commercial offerings and/or projects that began commercial service within the past ten years (James III PhD et al., 2019).
Nuclear, and biopower plantsThese are Annual Energy Outlook (EIA, 2021) reported costs.

Future Cost Projections for Renewables

The ATB future projections are based primarily on expert analysis, bottom-up modeling, and literature on specific technology innovations, which are described in detail for technology. The categories of innovations for each technology are shown in the following table. The innovations listed in these tables on each technology page, and summarized here, represent innovations that are assumed to drive most of the cost reductions in the ATB scenarios. These lists do not include all potential innovations, and they only include innovations that directly impact cost and performance.

Technology Innovations

Land-Based Wind

rotor, nacelle assembly

tower

science-based modeling

Offshore Wind

turbine size

supply chain

size-agnostic innovation

Solar Photovoltaics

module efficiency

inverter power electronics

installation efficiencies

energy yield gain

Concentrating Solar Power

power block

receiver

thermal storage

Solar Field

Geothermal

drilling advancements

enhanced geothermal system (EGS) development

Hydropower

learning by doing

modularity

new materials

automation/digitalization

eco-friendly turbines

Utility-Scale PV-Plus-BatterySee Solar Photovoltaics and Battery Storage rows.
Battery Storage

significant market demand (across electricity, EV and consumer electronics sectors)

improvements in chemistry 

supply chain development

Pumped-Storage Hydropower

modularity

new materials

automation/digitalization

eco-friendly turbines

Natural Gas and Coal

Estimates capture incremental cost reductions that occur over time (e.g., learning-by-doing improvements that are most often the result of more process design optimization and/or reduced costs that are due to improvements in equipment manufacturing practices) as well as deployment of advanced technologies that emerge from U.S. Department of Energy (DOE) Office of Fossil Energy and Carbon Management funded research and development (FE R&D). The Advanced Technology scenario reflects meeting relevant FE R&D program goals where second generation technologies become available beginning in 2025 and transformational technologies become available beginning in 2030. 

Future natural gas-fueled electricity generating options reflect cost and performance improvements in post-combustion carbon capture technologies followed by commercial deployments of advanced natural gas fuel cell (NGFC) systems equipped with carbon capture.

Future coal-fueled electricity generating options reflect cost and performance improvements in post-combustion carbon capture technologies as well as commercial deployments of advanced ultra-supercritical pulverized coal plants.

It is important to recognize that the estimates of future fossil performance and cost are based on deployment of representative technology pathways and should not be interpreted as representing the only technology pathways that align with FE R&D program goals. 

References

The following references are specific to this page; for all references in this ATB, see References.

James III PhD, Robert E., Dale Kearins, Marc Turner, Mark Woods, Norma Kuehn, and Alexander Zoelle. “Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity.” NETL, September 24, 2019. https://doi.org/10.2172/1569246.

Beiter, Philipp, Walt Musial, Patrick Duffy, Aubryn Cooperman, Matt Shields, Donna Heimiller, and Mike Optis. “The Cost of Floating Offshore Wind Energy in California between 2019 and 2032.” NREL Technical Report. Golden, CO, November 2020. https://www.nrel.gov/docs/fy21osti/77384.pdf.

Feldman, David, Vignesh Ramasamy, Ran Fu, Ashwin Ramdas, Jal Desai, and Robert Margolis. “U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2020.” National Renewable Energy Lab. (NREL), Golden, CO (United States), January 27, 2021. https://doi.org/10.2172/1764908.

Oladosu, G., George, L., and Wells, J. “2020 Cost Analysis of Hydropower Options at Non-Powered Dams.” Oak Ridge, TN: Oak Ridge National Laboratory, 2021.

EIA. “Annual Energy Outlook 2021.” Energy Information Administration, January 2021. https://www.eia.gov/outlooks/aeo/.

Stehly, Tyler, Philipp Beiter, and Patrick Duffy. “2019 Cost of Wind Energy Review.” Technical. National Renewable Energy Laboratory, December 2020. https://www.nrel.gov/docs/fy21osti/78471.pdf.

Mongird, Kendall, Vilayanur Viswanathan, Jan Alam, Charlie Vartanian, Vincent Sprenkle, and Richard Baxter. “2020 Grid Energy Storage Technology Cost and Performance Assessment.” USDOE, December 2020. https://www.energy.gov/energy-storage-grand-challenge/downloads/2020-grid-energy-storage-technology-cost-and-performance.

Turchi, Craig, Matthew Boyd, Devon Kesseli, Parthiv Kurup, Mark Mehos, Ty Neises, Prashant Sharan, Michael Wagner, and Timothy Wendelin. “CSP Systems Analysis: Final Project Report.” Technical Report. Golden, CO: National Renewable Energy Laboratory, May 2019. https://doi.org/10.2172/1513197.

O’Connor, Patrick W., Scott T. DeNeale, Dol Raj Chalise, Emma Centurion, and Abigail Maloof. “Hydropower Baseline Cost Modeling, Version 2.” Oak Ridge, TN: Oak Ridge National Laboratory, 2015. https://doi.org/10.2172/1244193.

DOE. “GeoVision: Harnessing the Heat Beneath Our Feet.” Washington, D.C.: U.S. Department of Energy, May 2019. https://www.energy.gov/sites/prod/files/2019/06/f63/GeoVision-full-report-opt.pdf.

Beiter, Philipp, Walter Musial, Aaron Smith, Levi Kilcher, Rick Damiani, Michael Maness, Senu Sirnivas, et al. “A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030.” Technical Report. Golden, CO: National Renewable Energy Laboratory, 2016. https://doi.org/10.2172/1324526.

DOE. “U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry.” Oak Ridge, TN: Oak Ridge National Laboratory, August 2011. https://doi.org/10.2172/1023318.

DOE. “Hydropower Vision: A New Chapter for America’s Renewable Electricity Source.” Washington, D.C.: U.S. Department of Energy, 2016. https://www.energy.gov/sites/prod/files/2018/02/f49/Hydropower-Vision-021518.pdf.

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